Monday, May 21, 2012
4:15 pm
105 Annenberg
Applied Mathematics Colloquium
Regularization of Positive Definite Matrices: Connections Between Algebra, Graph Theory and Statistics
Bala Rajaratnam, Statistics, Stanford University
Positive definite (p.d.) matrices arise naturally in many areas within
mathematics and also feature extensively in scientific applications,
including the earth sciences and biomedical sciences. In modern
high-dimensional applications, a common approach to finding sparse
positive definite matrices is to threshold their small off-diagonal
elements. This thresholding, sometimes referred to as
hard-thresholding, sets small elements to zero. Thresholding has the
attractive property that the resulting matrices are sparse, and are
thus easier to interpret and work with. In many applications, it is
often required, and thus implicitly assumed, that thresholded matrices
retain positive definiteness. In this paper we formally investigate
the algebraic properties of positive definite matrices which are
thresholded. Some interesting and unexpected results will be
presented. If time permits, probabilistic properties of thresholded
positive definite matrices and connections to optimization will also
be discussed.
(The presentation will be based on results from three papers: the first based on work by the speaker and D.Guillot, the second based on the work by the speaker, B.Naul, D.Guillot and A.Hero, and the third by the speaker.)
(The presentation will be based on results from three papers: the first based on work by the speaker and D.Guillot, the second based on the work by the speaker, B.Naul, D.Guillot and A.Hero, and the third by the speaker.)
Contact Sydney Garstang sydney@caltech.edu at x4555
For more information see http://www.acm.caltech.edu
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